Ovarian Cancer-Specific BRCA-like Copy-Number Aberration Classifiers Detect Mutations Associated with Homologous Recombination Deficiency in the AGO-TR1 Trial

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Ovarian Cancer-Specific BRCA-like Copy-Number Aberration Classifiers Detect Mutations Associated with Homologous Recombination Deficiency in the AGO-TR1 Trial. / Schouten, Philip C; Richters, Lisa; Vis, Daniel J; Kommoss, Stefan; van Dijk, Ewald; Ernst, Corinna; Kluin, Roelof J C; Marmé, Frederik; Lips, Esther H; Schmidt, Sandra; Scheerman, Esther; Prieske, Katharina; van Deurzen, Carolien H M; Burges, Alexander; Ewing-Graham, Patricia C; Dietrich, Dimo; Jager, Agnes; de Gregorio, Nikolaus; Hauke, Jan; du Bois, Andreas; Nederlof, Petra M; Wessels, Lodewyk F; Hahnen, Eric; Harter, Philipp; Linn, Sabine C; Schmutzler, Rita K.

in: CLIN CANCER RES, Jahrgang 27, Nr. 23, 01.12.2021, S. 6559-6569.

Publikationen: SCORING: Beitrag in Fachzeitschrift/ZeitungSCORING: ZeitschriftenaufsatzForschungBegutachtung

Harvard

Schouten, PC, Richters, L, Vis, DJ, Kommoss, S, van Dijk, E, Ernst, C, Kluin, RJC, Marmé, F, Lips, EH, Schmidt, S, Scheerman, E, Prieske, K, van Deurzen, CHM, Burges, A, Ewing-Graham, PC, Dietrich, D, Jager, A, de Gregorio, N, Hauke, J, du Bois, A, Nederlof, PM, Wessels, LF, Hahnen, E, Harter, P, Linn, SC & Schmutzler, RK 2021, 'Ovarian Cancer-Specific BRCA-like Copy-Number Aberration Classifiers Detect Mutations Associated with Homologous Recombination Deficiency in the AGO-TR1 Trial', CLIN CANCER RES, Jg. 27, Nr. 23, S. 6559-6569. https://doi.org/10.1158/1078-0432.CCR-21-1673

APA

Schouten, P. C., Richters, L., Vis, D. J., Kommoss, S., van Dijk, E., Ernst, C., Kluin, R. J. C., Marmé, F., Lips, E. H., Schmidt, S., Scheerman, E., Prieske, K., van Deurzen, C. H. M., Burges, A., Ewing-Graham, P. C., Dietrich, D., Jager, A., de Gregorio, N., Hauke, J., ... Schmutzler, R. K. (2021). Ovarian Cancer-Specific BRCA-like Copy-Number Aberration Classifiers Detect Mutations Associated with Homologous Recombination Deficiency in the AGO-TR1 Trial. CLIN CANCER RES, 27(23), 6559-6569. https://doi.org/10.1158/1078-0432.CCR-21-1673

Vancouver

Bibtex

@article{f1dfb3cc24f243459ec2ca785292376e,
title = "Ovarian Cancer-Specific BRCA-like Copy-Number Aberration Classifiers Detect Mutations Associated with Homologous Recombination Deficiency in the AGO-TR1 Trial",
abstract = "PURPOSE: Previously, we developed breast cancer BRCA1-like and BRCA2-like copy-number profile shrunken centroid classifiers predictive for mutation status and response to therapy, targeting homologous recombination deficiency (HRD). Therefore, we investigated BRCA1- and BRCA2-like classification in ovarian cancer, aiming to acquire classifiers with similar properties as those in breast cancer.Experimental Design: We analyzed DNA copy-number profiles of germline BRCA1- and BRCA2-mutant ovarian cancers and control tumors and observed that existing breast cancer classifiers did not sufficiently predict mutation status. Hence, we trained new shrunken centroid classifiers on this set and validated them in the independent The Cancer Genome Atlas dataset. Subsequently, we assessed BRCA1/2-like classification and obtained germline and tumor mutation and methylation status of cancer predisposition genes, among them several involved in HR repair, of 300 ovarian cancer samples derived from the consecutive cohort trial AGO-TR1 (NCT02222883).RESULTS: The detection rate of the BRCA1-like classifier for BRCA1 mutations and promoter hypermethylation was 95.6%. The BRCA2-like classifier performed less accurately, likely due to a smaller training set. Furthermore, three quarters of the BRCA1/2-like tumors could be explained by (epi)genetic alterations in BRCA1/2, germline RAD51C mutations and alterations in other genes involved in HR. Around half of the non-BRCA-mutated ovarian cancer cases displayed a BRCA-like phenotype.CONCLUSIONS: The newly trained classifiers detected most BRCA-mutated and methylated cancers and all tumors harboring a RAD51C germline mutations. Beyond that, we found an additional substantial proportion of ovarian cancers to be BRCA-like.",
author = "Schouten, {Philip C} and Lisa Richters and Vis, {Daniel J} and Stefan Kommoss and {van Dijk}, Ewald and Corinna Ernst and Kluin, {Roelof J C} and Frederik Marm{\'e} and Lips, {Esther H} and Sandra Schmidt and Esther Scheerman and Katharina Prieske and {van Deurzen}, {Carolien H M} and Alexander Burges and Ewing-Graham, {Patricia C} and Dimo Dietrich and Agnes Jager and {de Gregorio}, Nikolaus and Jan Hauke and {du Bois}, Andreas and Nederlof, {Petra M} and Wessels, {Lodewyk F} and Eric Hahnen and Philipp Harter and Linn, {Sabine C} and Schmutzler, {Rita K}",
note = "{\textcopyright}2021 The Authors; Published by the American Association for Cancer Research.",
year = "2021",
month = dec,
day = "1",
doi = "10.1158/1078-0432.CCR-21-1673",
language = "English",
volume = "27",
pages = "6559--6569",
journal = "CLIN CANCER RES",
issn = "1078-0432",
publisher = "American Association for Cancer Research Inc.",
number = "23",

}

RIS

TY - JOUR

T1 - Ovarian Cancer-Specific BRCA-like Copy-Number Aberration Classifiers Detect Mutations Associated with Homologous Recombination Deficiency in the AGO-TR1 Trial

AU - Schouten, Philip C

AU - Richters, Lisa

AU - Vis, Daniel J

AU - Kommoss, Stefan

AU - van Dijk, Ewald

AU - Ernst, Corinna

AU - Kluin, Roelof J C

AU - Marmé, Frederik

AU - Lips, Esther H

AU - Schmidt, Sandra

AU - Scheerman, Esther

AU - Prieske, Katharina

AU - van Deurzen, Carolien H M

AU - Burges, Alexander

AU - Ewing-Graham, Patricia C

AU - Dietrich, Dimo

AU - Jager, Agnes

AU - de Gregorio, Nikolaus

AU - Hauke, Jan

AU - du Bois, Andreas

AU - Nederlof, Petra M

AU - Wessels, Lodewyk F

AU - Hahnen, Eric

AU - Harter, Philipp

AU - Linn, Sabine C

AU - Schmutzler, Rita K

N1 - ©2021 The Authors; Published by the American Association for Cancer Research.

PY - 2021/12/1

Y1 - 2021/12/1

N2 - PURPOSE: Previously, we developed breast cancer BRCA1-like and BRCA2-like copy-number profile shrunken centroid classifiers predictive for mutation status and response to therapy, targeting homologous recombination deficiency (HRD). Therefore, we investigated BRCA1- and BRCA2-like classification in ovarian cancer, aiming to acquire classifiers with similar properties as those in breast cancer.Experimental Design: We analyzed DNA copy-number profiles of germline BRCA1- and BRCA2-mutant ovarian cancers and control tumors and observed that existing breast cancer classifiers did not sufficiently predict mutation status. Hence, we trained new shrunken centroid classifiers on this set and validated them in the independent The Cancer Genome Atlas dataset. Subsequently, we assessed BRCA1/2-like classification and obtained germline and tumor mutation and methylation status of cancer predisposition genes, among them several involved in HR repair, of 300 ovarian cancer samples derived from the consecutive cohort trial AGO-TR1 (NCT02222883).RESULTS: The detection rate of the BRCA1-like classifier for BRCA1 mutations and promoter hypermethylation was 95.6%. The BRCA2-like classifier performed less accurately, likely due to a smaller training set. Furthermore, three quarters of the BRCA1/2-like tumors could be explained by (epi)genetic alterations in BRCA1/2, germline RAD51C mutations and alterations in other genes involved in HR. Around half of the non-BRCA-mutated ovarian cancer cases displayed a BRCA-like phenotype.CONCLUSIONS: The newly trained classifiers detected most BRCA-mutated and methylated cancers and all tumors harboring a RAD51C germline mutations. Beyond that, we found an additional substantial proportion of ovarian cancers to be BRCA-like.

AB - PURPOSE: Previously, we developed breast cancer BRCA1-like and BRCA2-like copy-number profile shrunken centroid classifiers predictive for mutation status and response to therapy, targeting homologous recombination deficiency (HRD). Therefore, we investigated BRCA1- and BRCA2-like classification in ovarian cancer, aiming to acquire classifiers with similar properties as those in breast cancer.Experimental Design: We analyzed DNA copy-number profiles of germline BRCA1- and BRCA2-mutant ovarian cancers and control tumors and observed that existing breast cancer classifiers did not sufficiently predict mutation status. Hence, we trained new shrunken centroid classifiers on this set and validated them in the independent The Cancer Genome Atlas dataset. Subsequently, we assessed BRCA1/2-like classification and obtained germline and tumor mutation and methylation status of cancer predisposition genes, among them several involved in HR repair, of 300 ovarian cancer samples derived from the consecutive cohort trial AGO-TR1 (NCT02222883).RESULTS: The detection rate of the BRCA1-like classifier for BRCA1 mutations and promoter hypermethylation was 95.6%. The BRCA2-like classifier performed less accurately, likely due to a smaller training set. Furthermore, three quarters of the BRCA1/2-like tumors could be explained by (epi)genetic alterations in BRCA1/2, germline RAD51C mutations and alterations in other genes involved in HR. Around half of the non-BRCA-mutated ovarian cancer cases displayed a BRCA-like phenotype.CONCLUSIONS: The newly trained classifiers detected most BRCA-mutated and methylated cancers and all tumors harboring a RAD51C germline mutations. Beyond that, we found an additional substantial proportion of ovarian cancers to be BRCA-like.

U2 - 10.1158/1078-0432.CCR-21-1673

DO - 10.1158/1078-0432.CCR-21-1673

M3 - SCORING: Journal article

C2 - 34593530

VL - 27

SP - 6559

EP - 6569

JO - CLIN CANCER RES

JF - CLIN CANCER RES

SN - 1078-0432

IS - 23

ER -